Decoding the Age Within
Chronological age, measured from the time of birth, has long been a standard metric in healthcare and aging research. However, it is an imperfect measure, lacking the nuanced information provided by biological age, which considers various genetic and environmental factors. Biological age estimates are generated through mathematical models that use biomarkers as predictors and chronological age as the output. The difference between biological and chronological age—known as the “age gap”—serves as a complementary indicator of aging, offering additional insights beyond the limitations of chronological age alone. The utility of the "age gap" becomes evident when examining its correlation with specific exposures, like lifestyle choices or pre-existing health conditions. For instance, in brain age estimation, neuroimaging biomarkers are used as predictors. The "brain age gap" between model-predicted age and chronological age serves as an avenue to study the impact of gene